MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning

• URL: http://arxiv.org/abs/2607.26465v1
• Date: Wed, 29 Jul 2026 04:37:59 GMT
• Title: MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning
• Abstract summary: Multimodal Large Language Models have sparked significant interest due to their potential for social intelligence.<n>We introduce MultivationBench, a benchmark designed to rigorously evaluate multimodal motivation reasoning within story-driven visual narratives.<n>Results indicate that MultivationBench presents a significant challenge: all tested models struggle to maintain consistent motivation reasoning across sequential contexts.
• Score: 53.157837009685466
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Multimodal Large Language Models have sparked significant interest due to their potential for social intelligence; however, their ability to perform sequential motivation reasoning remains insufficiently studied. Existing evaluations predominantly examine static text or isolated visual snapshots, which do not reflect the cumulative nature of real-world behavioral drivers. To address this gap, we introduce MultivationBench, a benchmark designed to rigorously evaluate multimodal motivation reasoning within story-driven visual narratives. The benchmark builds upon established psychological frameworks - Maslow's hierarchy and Reiss's basic desires - and requires models to integrate accumulated multimodal context to infer evolving motivations. Results indicate that MultivationBench presents a significant challenge: all tested models struggle to maintain consistent motivation reasoning across sequential contexts, revealing a critical disconnect between static recognition capabilities and the dynamic reasoning essential for human-like social understanding.

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